Egg Mass Detection Using AI Image Processing
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Solution Overview
Problem
Existing methods for processing avian eggs, such as egg classification and mass determination, are inefficient and lack accuracy, especially when dealing with a large number of eggs.
Innovation Solution
A method and system that convey eggs along a path, generate multiple images of each egg from different sides using illumination light, and process these images using a digital image processor and a trained learning model, such as a Convolutional Neural Network (CNN), to determine the egg mass accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to determine egg mass, then processing speed is relatively fast, but measurement precision is insufficient and accuracy is low
Solution Approach 1:
The patent replaces traditional mechanical/image processing mass determination methods with an AI-based neural network system. The neural network is trained on large datasets of egg images and corresponding masses, enabling it to predict egg mass with high accuracy (standard deviation of 1 gram or better) while maintaining real-time processing capability. This substitution of AI algorithms for traditional image analysis resolves the contradiction between measurement precision and productivity.
2Measurement precision
If multiple images are taken from different angles to improve mass estimation accuracy, then measurement precision improves, but processing time increases
Solution Approach 1:
The patent performs preliminary action by capturing multiple images of each egg from different angles before processing. These pre-captured images are then fed into the trained neural network model for simultaneous processing. The neural network efficiently analyzes all images and determines mass with high accuracy (standard deviation of 1 gram or better) without requiring sequential processing, thus resolving the time-accuracy trade-off through parallel processing capability of the AI model.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables reliable and efficient egg mass estimation with high accuracy, achieving a low standard deviation of 1 gram or better, and allows for real-time processing of a large number of eggs.
Implementation Method 1
generating a plurality of images of each egg from different sides of the egg using illumination light
Data Source
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AI summary
Method for processing a plurality of avian eggs, in particular unfertilized eggs, including: -conveying each egg (E) along a conveying path; -generating a plurality of images of each egg (E) from different sides of the egg using illumination light (B); and processing the plurality of images of each egg (E), by a digital image processor (8), utilizing a trained learning model to determine a mass of the egg, and outputting the determined mass of the egg, for example for classifying the egg.